Virtual Instrumentation Based Brain Tumor Detection, Analysis and Identification

Authors

  • Saylee R Lad  M.Tech Electronics, Electrical Engineering Dept., VJTI, Mumbai, India
  • Dr Prof M S Panse  Professor, Electrical Engineering Dept., VJTI, Mumbai, India

Keywords:

Brain Tumor, Image processing, MRI, Filtering, Segmentation, SVM

Abstract

End to end mechanism of automating the tumor detection and classifying the tumor cells is carried out in this paper. Denoising followed by image enhancement and segmentation is used for tumor detection. Comparative evaluation of segmentation techniques is carried out which include Thresholding, Watershed algorithm, K- means, Fuzzy C. Performance of segmentation algorithm is evaluated by accuracy analysis. Fuzzy C is proved to be the best segmentation technique for brain tumor detection. Different parameters are extracted from the detected tumor which is used to train the Support Vector Machine. Designed Support Vector Machine is then used to determine tumor type whether benign or malignant.

References

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International Journal of Scientific Research in Science and Technology

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Published

2018-06-30

Issue

Volume 4, Issue 8, May-June-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Saylee R Lad, Dr Prof M S Panse, " Virtual Instrumentation Based Brain Tumor Detection, Analysis and Identification, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 8, pp.581-590, May-June-2018.